Process Mining Software

Process mining software needs to be able to deal with log files of most popular software used at your company. In most companies, these include:

• Customer Relationship Management (CRM) software
• Enterprise Resource Planning (ERP) software
• Customer support software
• Accounting/financial management software
• Email and other communication software

Please note that this is a very high level list. IT department should be able to provide a more comprehensive list. Then, you can provide this list to process mining vendors so they can identify the software which their product already works with.

Focusing purely on processes without paying attention to the business value of processes can lead companies to sub-optimize their process mining efforts. Aligning on business priorities before starting process mining would help teams focus on critical areas.

Different alternatives can provide different functionality provided by process mnining software. However, these approaches tend to be more expensive than process mining

• Methodologies such as Lean Management, 6 Sigma or Toyota Production System, Total Quality Management (TQM), Plan-Do-Check-Act (PDCA) can all be used for process optimization. However, these are more manual approaches which can be more expensive to implement. These methodologies can be implemented without relying on analysis of detailed system logs as they can also rely on higher level KPIs for performance measurement. Performance data can be compared in light of documented process flows to identify bottlenecks and improvement areas. However, these approaches can be more efficient if they can use data and insights provided by process mining software.

   

• Process discovery can be achieved via interviews and observations. DILO (Day In the Life Of) is a common approach which involves process specialists spending a few hours with the process owners to understand how the process flows
• There are numerous approaches for conformance checking such as controls built into systems for automated process conformance checks.

Benefits include

• Faster, more effective and more efficient processes thanks to process optimization
• Comformance checking improves compliance
• Process discovery enables faster automation of processes

You can refer to our process mining benefits guide to learn 10+ benefits of process mining software.

Process mining manifesto published by Institute of Electrical and Electronic Engineers (IEEE) task force on process mining, lays out the premise and principles that continue to guide process mining today.

Process mining book and the book's online course prepared by Wil van der Aalst, one of the leaders in process mining research are detailed guides into process mining.

Process mining software analyze event logs which store detailed, time series data about events. As a result of this analysis, process mining software can prepare a workflow for the process, suggest process improvements or measure conformance of process to provided guidelines

Process mining tools prepare workflows by mapping events in logs to activities and individual cases. Therefore, a map of cases can be created which shows both most common cases (e.g. processing an invoice by a supplier in company's supplier database) and rare cases (e.g. processing an invoice by a new supplier). Feel free to read the related section of our article to learn more.

Figure:An individual case shown in process mining software Celonis' interface

Figure:Process map with all cases overlaid. Source: Celonis

Interest in process mining is increasing because it helps companies automate and optimize repetitive back office processes. Back office processes are being automated at an increased rate since the 2010s with the emergence of technologies such as RPA and commercialization of AI.

Process optimization has always been a focus point for companies. However, initially process optimization was focused on blue collar tasks. Since 1950s, businesses heavily invested in process optimization and companies like Toyota rose to market leadership positions from obscurity partially thanks to their focus on process. Since 1950s, a number of approaches to process optimization have achieved popularity including Toyota Production System, Six Sigma and Lean Manufacturing

Thanks to emerging technologies such as RPA (robotic process automation), that increased in popularity in the 2010s, it is increasingly possible to automate white collar tasks. According to our interviews with the Automation Anywhere product team, with RPA processes such as invoice to pay can achieve STP (Straight Through Processing) rates of >70%, meaning that 70% of invoices get paid with no manual intervention.

Commercialization of AI is also contributing to process mining in 2 ways. First, improved AI applications are driving back office automation which is driving the need for better understanding of processes. Secondly, improved AI and machine learning approaches are improving the effectiveness of process mining tools.

Process mining software enable process improvement and automation since detailed data in process logs help identify process inefficiencies and automatable processes. Without these insights, automation projects can focus on the wrong processes, partially automate processes or automate processes that have not been fully optimized.

You can read more about this question in the related section of our ultimate process mining guide.

As in any PoC, it is helpful to have a list of goals/assessment areas with quantifiable values. This enables different PoCs to be be compared and PoC to be useful during vendor selection.

In case of process mining software, PoC should be mainly focused on assessing usability and effectiveness.

The best way to assess usability is to have the team that will use the product to build a project with it. This project should focus on one of process mining use cases that your organization chose to prioritize. After the project, they should assess the software using the list they prepared in advance which should allow for objective assessment of different software.

The project results would be evaluated by top management to assess usefulness of the effort. Again, a scoring guideline prepared before the PoC would help evaluate whether the process mining software is a worthwhile investment.

Process mining software would be beneficial for companies with

• a large back office (>100 employees)
• processes that were designed a few years ago
• aims to increase the level automation

However, ROI of such initiatives are hard to measure as most benefits are qualitative or difficult to directly measure. A lean approach to estimate the value of such initiatives is to assign them to a relatively junior team member or intern. Top management should guide the pilot with steering meetings and estimate the impact of the initative at the end of the project. If project looks promising, more expensive team members can be deployed to the project to maximize its benefits

Process mining software support the analysis and optimization of business processes based on event logs.

Processes are important for companies. "Focus on the process not outcome" is commonly accepted knowledge. We can't control the outcomes, inevitably there will be variation in outcomes. However, we can control the process which can yield better outcomes.

Though processes are important, they are almost always poorly documented. This is because:

• Preparing process documentation is labor-intensive.
• Processes change due to market demands, regulation and companies' evolving strategies.

Process mining software helps companies remain informed about their processes and to continuously optimize and automate them.

Process mining is also called Automated Business Process Discovery (ABPD). If you want to learn more, you can read our related article.

Any industry that relies on common software systems like CRM or ERP can benefit from process mining.

There are 6 ways to use process mining software:

• Process discovery to enable process automation: For processes to be automated, the process flows and exceptions need to be identified. Process mining software can be used to automatically prepare an estimated process flow. This flow can guide teams using technologies such as RPA to automate processes.
• Process discovery to enable decision automation: Human decision making is slow, expensive and hard to standardize. Therefore decision automation is valuable and process logs can enable this. Process mining software can identify both the available data at decision time and the decisions taken as well as results of such decisions. This data can be used to train and develop machine learning models which can automate those decisions.
• Process optimization: Process performance metrics can be inferred from logs and this data can be used to identify bottlenecks and costly steps to optimize speed, efficiency or outcomes of the process.
• Conformance validation: If the process is already defined and documented, process logs can be examined to check whether process was completed according to specifications. For example, purchasing decisions require different approvals based on ticket size and nature of the item purchased. Logs can be checked if necessary approvals are taken
• Process simulation: While other use cases involve analysis of past processes, in simulation predictive algorithms can be employed to identify situations and cases that cause bottlenecks or excessive costs. Additionally, simulations can predict future outcomes, better informing process stakeholders and customers. For example, the customer can recieve an accurate estimate of when her loan application will be processed.
• Organizational mining:Process logs can identify organizational relationships, performance gaps and best practices. While process optimization software is mostly related to process, almost all processes have a human component which can not be ignored. Process data can be used to understand and improve human aspects of processes.

For more use cases, feel free to read our in-depth guide that includes 30+ process mining use cases.

Software deployment best practices would need to be followed and process owners and IT would need to be involved in rolling out the process mining solution. Depending on company's prioritized use cases for process mining software, other teams may need to be involved:

• Process discovery to enable process automation: Automation or RPA Center of Excellence (CoE) or company's RPA consultants or the teams working on process automation would benefitfrom process mining. It would help them undestand the processes they are automating.
• Process discovery to enable decision automation: Data science and analytics teams.
• Process optimization and simulation:Responsibility for process optimization lies under CFO, COO or HR in different organizations. The team responsible for process optimization can benefit from process mining as it will help them understand the processes and measure the impact of their process optimization efforts.
• Conformance validation:Controlling function can leverage process mining to monitor compliance issues in processes where making process and system changes to minimize compliance issues is prohibitively expensive.
• Organizational mining:HR can rely on organizational mining to bring more data to its decision making

IT, non-IT teams that are responsible for process optimization and process owners can use process mining software. Since most process mining software vendors focus on usability and since process mining is non-invasive (i.e. does not make changes to systems or databases), it can be used by non-technical users.

On top of usual tech procurement best practices, features and integrations are the 2 areas where attention is required in selecting the right process mining software.

Selected process mining software should be providing the necessary features to realize your organization's prioritized use cases. Your organization first needs to decide the specific use cases they will use process mining software for. We explained in other answers both process mining use cases and how these use cases are mapped to features.

Selected process mining software should be able to process logs of software that are commonly used in your company. Without this, process mining software will require more manual intervention while extracting insights from software logs.

Necessary feature set to enable key usecases include the below items. However, process mining is an emerging field and not all vendors offer all of these features.

• Overall:
  • An easy-to-use user interface (UI)
  • Integration with major ERP, CRM and other popular software to enable automated log file processing
  • Data preparation, data cleansing and automated event tagging support to analyze log files from unsupported software modules
  • Flexible real-time dashboards with support for key performance indicators (KPIs)
  • Support for modelling the interaction of different processes
• Process discovery

• Automated discovery of process maps and analytical capability to highlight cases by frequency
• Capability to map customer customer journey maps on top of internal processes
• Predictive analytics/machine learning capabilities to identify decision making rules from log files

• Automated process optimization suggestions
• Conformance validation capabilities
• Predictive/prescriptive analytics capabilities to enable simulations
• Organizational mining

• Integration with common HR platform to auto extract organizational data
• Identification of personnel with responsibilities across processes
• Personnel performance management across different units and locations

You can read the related section of our process mining guide to learn more.